Multi-Agent Systems & Coordination in Python Training Course
This course delves into the design, coordination, and implementation of multi-agent systems (MAS) using Python. Participants will gain insights into constructing agents that communicate, collaborate, and adapt to achieve shared objectives within complex, dynamic environments.
This instructor-led, live training (available online or onsite) is tailored for advanced-level professionals seeking to design and implement multi-agent systems for intelligent automation, simulation, and decision-making applications.
Upon completion of this training, participants will be able to:
- Comprehend the architecture and fundamental principles of multi-agent systems.
- Develop agents capable of communication, coordination, and negotiation.
- Implement distributed environments for agent interactions.
- Apply reinforcement learning and planning techniques in multi-agent contexts.
- Simulate cooperative and competitive agent behaviors.
- Design hybrid workflows that integrate humans and intelligent agents.
Format of the Course
- Instructor-led lectures and live demonstrations.
- Hands-on exercises using open-source agent frameworks.
- Applied group project simulating a multi-agent scenario.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Course Outline
Introduction to Multi-Agent Systems
- Overview of agents, environments, and interaction models
- Cooperation, competition, and autonomy in agentic systems
- Applications in logistics, robotics, and decision-making
Core Concepts of Agent Architecture
- Reactive vs. deliberative agents
- Communication protocols and coordination models
- Knowledge representation and shared state
Implementing Agents in Python
- Building agents using the Mesa framework
- Modeling environments and interactions
- Simulating agent behavior and visualization
Coordination and Communication
- Message passing and shared memory architectures
- Negotiation, consensus, and task allocation
- Coordination algorithms (contract net, market-based, swarm models)
Learning and Adaptation in Multi-Agent Systems
- Reinforcement learning for multiple agents
- Cooperative vs. competitive learning dynamics
- Using PettingZoo and Stable-Baselines3 for MARL
Distributed Computing and Scaling
- Using Ray for distributed multi-agent simulations
- Managing concurrency and synchronization
- Parallelizing computation and handling shared resources
Human–Agent Collaboration
- Designing interfaces for human-in-the-loop coordination
- Hybrid workflows with AI-assisted decision support
- Ethical and operational considerations
Capstone Project
- Design and implement a multi-agent system in Python
- Demonstrate coordination and learning among agents
- Present simulation results and performance insights
Summary and Next Steps
Requirements
- Strong proficiency in Python programming
- Good understanding of reinforcement learning or AI agent design
- Familiarity with distributed systems and networking concepts
Audience
- System architects designing collaborative or distributed AI systems
- Researchers working on coordination and collective intelligence
- Engineers developing hybrid human–agent or multi-agent workflows
Open Training Courses require 5+ participants.
Multi-Agent Systems & Coordination in Python Training Course - Booking
Multi-Agent Systems & Coordination in Python Training Course - Enquiry
Multi-Agent Systems & Coordination in Python - Consultancy Enquiry
Upcoming Courses
Related Courses
Agentic Development with Gemini 3 and Google Antigravity
21 HoursGoogle Antigravity is an agentic development environment designed to build autonomous agents capable of planning, reasoning, coding, and acting through Gemini 3’s multimodal capabilities.
This instructor-led, live training (online or onsite) is aimed at advanced-level technical professionals who wish to design, build, and deploy autonomous agents using Gemini 3 and the Antigravity environment.
Upon finishing this training, participants will be prepared to:
- Build autonomous workflows that use Gemini 3 for reasoning, planning, and execution.
- Develop agents in Antigravity that can analyze tasks, write code, and interact with tools.
- Integrate Gemini-driven agents with enterprise systems and APIs.
- Optimize agent behavior, safety, and reliability in complex environments.
Format of the Course
- Expert demonstrations combined with interactive discussions.
- Hands-on experimentation with autonomous agent development.
- Practical implementation using Antigravity, Gemini 3, and supporting cloud tools.
Course Customization Options
- If your team requires domain-specific agent behaviors or custom integrations, please contact us to tailor the program.
Advanced Antigravity: Feedback Loops, Learning & Long-Term Agent Memory
14 HoursGoogle Antigravity represents a sophisticated framework designed for experimenting with long-lived agents and emergent interactive behaviors.
This instructor-led training, available either online or onsite, is tailored for advanced professionals seeking to design, analyze, and optimize agents that can retain memories, improve via feedback, and evolve across extended operational periods.
After completing this course, participants will be equipped with the following skills:
- Constructing long-term memory structures to ensure agent persistence.
- Implementing effective feedback loops to guide and shape agent behavior.
- Assessing learning trajectories and monitoring model drift.
- Integrating memory mechanisms within complex multi-agent ecosystems.
Course Format
- Expert-led discussions complemented by technical demonstrations.
- Practical exploration through structured design challenges.
- Application of learned concepts to simulated agent environments.
Customization Options
- For organizations requiring tailored content or specific case studies, please contact us to arrange customized training.
Antigravity for Developers: Building Agent-First Applications
21 HoursAntigravity serves as a development platform specifically engineered for creating AI-driven, agent-first applications.
This instructor-led training, available either online or onsite, targets intermediate-level developers looking to build real-world applications utilizing autonomous AI agents within the Antigravity ecosystem.
Upon completing this training, participants will be capable of:
- Developing applications that depend on autonomous and coordinated AI agents.
- Utilizing the Antigravity IDE, editor, terminal, and browser for comprehensive development.
- Overseeing multi-agent workflows via the Agent Manager.
- Integrating agent functionalities into production-ready software systems.
Course Format
- A mix of presentations accompanied by detailed demonstrations.
- Substantial hands-on practice with guided exercises.
- Practical implementation work within the live Antigravity environment.
Customization Options
- For content tailored to your specific development stack, please reach out to us to arrange a customized training session.
Getting Started with Antigravity: An Introduction to Agent-First IDEs
14 HoursGoogle Antigravity is an agent-first development environment designed to streamline engineering workflows through intelligent automation.
This instructor-led, live training (online or onsite) is aimed at beginner-level practitioners who wish to explore the fundamentals of Antigravity and understand how agent-driven coding environments enhance productivity.
Upon completion of this training, participants will be able to:
- Install and configure Google Antigravity.
- Navigate and understand both the Editor View and Manager View.
- Work effectively with agents to automate simple development tasks.
- Use Antigravity to generate, refine, and manage project files.
Format of the Course
- Instructor explanations supported by real-time demonstrations.
- Guided exercises focused on hands-on use of agents.
- Practical exploration of core Antigravity features in a controlled lab environment.
Course Customization Options
- If you require a tailored version of this training, please contact us to arrange a customized program.
Antigravity for Web Automation & Browser-Based Tasks
21 HoursGoogle Antigravity serves as a platform designed for developing agents that can interact with web applications, browser environments, and multi-surface workflows.
This instructor-led training session, available both online and on-site, is tailored for intermediate-level professionals looking to build, automate, and test workflows within browser environments using Google Antigravity.
Upon completing the training, participants will be equipped to:
- Develop agents capable of interacting with web applications within a browser interface.
- Automate end-to-end workflows across various browser contexts.
- Validate and troubleshoot agent performance in UI-driven settings.
- Deploy cross-surface automation strategies utilizing Antigravity.
Course Format
- Guided instruction complemented by live demonstrations.
- Practical, hands-on activities and scenario-based exercises.
- Implementation of agent workflows within an interactive lab environment.
Customization Options
- For specific training needs, please contact us to customize the course according to your objectives.
Governance and Security Patterns for WrenAI in the Enterprise
14 HoursWrenAI is an AI-driven analytics platform built to connect data, model insights, and generate dashboards. In enterprise settings, strong governance and security are essential for safe and compliant adoption.
This instructor-led, live training (available online or onsite) targets advanced-level enterprise professionals looking to implement governance, compliance, and security patterns for WrenAI at scale.
By the end of this training, participants will be able to:
- Design and implement permissioning models in WrenAI.
- Apply auditability and monitoring practices for compliance.
- Set up secure environments with enterprise-level controls.
- Roll out WrenAI safely across large organizations.
Course Format
- Interactive lecture and discussion.
- Hands-on labs with governance and security configurations.
- Practical exercises simulating enterprise rollout scenarios.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Modernizing Legacy BI with WrenAI: Adoption, Migration, and Change Management
14 HoursWrenAI empowers organizations to transition from static dashboards to conversational analytics and embedded generative BI. This shift demands strategic adoption planning, seamless asset migration, and robust change management practices.
This instructor-led live training (available online or onsite) targets intermediate BI and data platform professionals seeking to modernize their legacy BI systems using WrenAI.
Upon completing this training, participants will be capable of:
- Assessing legacy BI environments to pinpoint modernization opportunities.
- Strategically planning and executing the migration from static dashboards to WrenAI.
- Implementing conversational analytics and embedded GenBI functionalities.
- Leading organizational change management initiatives for BI modernization.
Course Format
- Interactive lectures and discussions.
- Practical exercises focused on migration and adoption planning.
- Hands-on labs covering conversational analytics and embedded GenBI.
Customization Options
- For tailored training solutions, please reach out to us to arrange a schedule.
Quality and Observability for WrenAI: Evaluation, Prompt Tuning, and Monitoring
14 HoursWrenAI facilitates the conversion of natural language into SQL queries and provides AI-driven analytics, streamlining data access and enhancing its intuitiveness. For enterprise-level deployments, rigorous quality assurance and observability practices are critical to guaranteeing precision, dependability, and regulatory compliance.
This instructor-led, live training session (available online or on-site) is designed for advanced data and analytics professionals seeking to assess query accuracy, implement prompt optimization techniques, and establish observability protocols to monitor WrenAI in production environments.
Upon completion of this training, participants will be equipped to:
- Assess the precision and reliability of Natural Language to SQL outputs.
- Utilize prompt optimization strategies to enhance system performance.
- Track deviations and query patterns over time.
- Integrate WrenAI with logging and observability frameworks.
Training Structure
- Interactive lectures and discussions.
- Practical exercises focusing on evaluation and optimization techniques.
- Hands-on labs dedicated to observability and monitoring integrations.
Customization Options
- To arrange tailored training for this course, please get in touch with us.
Building with the WrenAI API: Applications, Charts, and NL to SQL
14 HoursThe WrenAI API serves as a robust interface for converting natural language into SQL queries, developing custom applications, and embedding charts within internal platforms.
This instructor-led, live training session, available online or on-site, is designed for intermediate-level engineers looking to leverage the WrenAI API for practical use cases, such as SQL generation, data visualization, and application integration.
Upon completing this training, participants will be capable of:
- Authenticating and linking applications to the WrenAI API.
- Creating SQL queries from natural language inputs.
- Creating and embedding visualizations via API endpoints.
- Integrating WrenAI into backend systems and internal tools.
Course Format
- Interactive lectures and discussions.
- Practical exercises involving API calls and integrations.
- Hands-on projects connecting applications, visualizations, and data pipelines.
Customization Options
- To request a tailored training session for this course, please contact us to arrange it.
WrenAI Cloud Essentials: From Data Sources to Dashboards
14 HoursWrenAI Cloud is a contemporary platform designed for linking data sources, modeling data, and constructing interactive dashboards.
This instructor-led, live training (available online or onsite) is designed for beginner to intermediate data professionals seeking to master setting up WrenAI Cloud, modeling data, and visualizing insights via dashboards.
Upon completion of this training, participants will be able to:
- Set up and configure WrenAI Cloud environments.
- Connect WrenAI Cloud to various data sources.
- Model data and establish relationships for analytics.
- Create interactive dashboards for business insights.
Format of the Course
- Interactive lecture and discussion.
- Hands-on cloud platform configuration and data modeling.
- Practical exercises in dashboard building and visualization.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
WrenAI for Financial Analytics: KPI Modeling and Regulatory-Aware Dashboards
14 HoursWrenAI empowers finance teams to model key performance indicators (KPIs), integrate standardized metrics, and construct dashboards that adhere to regulatory requirements and audit standards.
This instructor-led live training, available either online or onsite, targets intermediate to advanced finance professionals seeking to leverage WrenAI for creating compliant financial data models and dashboards that facilitate decision-making and risk management.
Upon completion of this training, participants will be capable of:
- Modeling financial KPIs and metrics within WrenAI.
- Developing dashboards that align with regulatory and audit mandates.
- Integrating WrenAI with financial data sources to enable real-time reporting.
- Implementing best practices for financial analytics and risk monitoring.
Course Format
- Interactive lectures and discussions.
- Practical exercises involving financial data models.
- Hands-on labs focused on dashboard design and compliance reporting.
Customization Options
- For organizations interested in tailored training for this course, please reach out to us to arrange a customized session.
WrenAI OSS Deep Dive: Semantic Modeling, Text to SQL, and Guardrails
21 HoursWrenAI is an open-source generative business intelligence (BI) tool that facilitates the conversion of natural language into SQL queries and supports semantic data modeling.
This instructor-led live training, available online or on-site, is designed for advanced-level data engineers, analytics engineers, and machine learning engineers who aim to construct robust semantic layers, refine prompts, and guarantee reliable SQL generation.
Upon completion of this training, participants will be capable of:
- Implementing semantic models to ensure consistent metric definitions across various teams.
- Enhancing text-to-SQL performance to achieve higher accuracy and scalability.
- Configuring and enforcing safety guardrails to prevent invalid or hazardous queries.
- Seamlessly integrating WrenAI OSS into data pipelines and analytics workflows.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical application.
- Hands-on implementation within a live laboratory environment.
Customization Options
- For those interested in a customized training session for this course, please contact us to arrange it.
WrenAI for Product Teams: Conversational Analytics and Self-Service BI
14 HoursWrenAI is a conversational analytics platform that translates natural-language queries into reliable analytics, enabling non-technical teams to generate insights quickly and consistently.
This instructor-led, live training (online or onsite) is aimed at intermediate-level product managers, analysts, and data champions who wish to adopt conversational analytics and build self-service BI capabilities with WrenAI.
By the end of this training, participants will be able to:
- Design conversational analytics workflows that surface reliable product insights.
- Create and maintain a standardized metrics layer for consistent reporting.
- Use natural-language to SQL features effectively to answer product questions.
- Embed WrenAI-driven self-service dashboards and guardrails in product workflows.
Format of the Course
- Interactive lecture and discussion.
- Hands-on labs with Wren AI and sample datasets.
- Workshop: build a self-service dashboard and conversational query set.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Deploying WrenAI for SaaS: Embedded GenBI in Customer-Facing Products
14 HoursWrenAI empowers SaaS providers to seamlessly embed generative business intelligence (GenBI) directly into their customer-facing applications. This course provides SaaS teams with the essential skills to integrate WrenAI via its Embedded API, configure white-label analytics, and manage multi-tenant deployments effectively.
Delivered as an instructor-led live training (available online or onsite), this program is designed for intermediate to advanced SaaS product leaders, data engineers, and full-stack developers who aim to deploy WrenAI as an embedded analytics solution within SaaS ecosystems.
Upon completing this training, participants will be equipped to:
- Integrate WrenAI using the Embedded API for customer-facing applications.
- Implement white-label conversational BI with customized branding and design.
- Design secure and scalable multi-tenant deployment architectures.
- Monitor usage metrics, optimize performance, and ensure regulatory compliance in SaaS environments.
Course Format
- Interactive lectures and group discussions.
- Practical labs utilizing the WrenAI Embedded API.
- Workshop: Design and deploy a white-label analytics feature tailored for a specific SaaS use case.
Customization Options
- To request a customized training session for this course, please contact us to arrange your specific requirements.
Operational Analytics with WrenAI Spreadsheets and Metrics Library
14 HoursWrenAI Spreadsheets and Metrics Library facilitate rapid reporting by utilizing AI-driven spreadsheet workflows and a repository of pre-established, cross-platform business metrics.
This instructor-led live training, available online or on-site, is designed for operations professionals at beginner to intermediate levels who aim to speed up their reporting and analysis processes using WrenAI Spreadsheets alongside the Metrics Library.
Upon completion of this training, participants will be equipped to:
- Construct AI-enhanced spreadsheets tailored for data analysis and reporting.
- Utilize the WrenAI Metrics Library to implement standardized Key Performance Indicators (KPIs).
- Link spreadsheets with various data sources to ensure real-time updates.
- Develop automated workflows to streamline operational reporting efforts.
Format of the Course
- Interactive lectures and discussions.
- Practical, hands-on experience building spreadsheets with WrenAI.
- Practical exercises focused on metrics and KPI reporting.
Course Customization Options
- To request a customized training version of this course, please contact us to arrange it.